Jan 2018 - Tech Buyer Presentation - Doc # AP42219717
IDC FutureScape: Worldwide Datacenter 2018 Predictions — APEJ Implications
By: Glen DuncanAssociate Research Director, Avneesh SaxenaGroup Vice President, Domain Research Group, IDC Asia/Pacific, Jun Fwu ChinResearch Director, Cynthia HoResearch Manager, Enterprise Servers Enterprise Server and Data Center Research Group, Annemarie AJ Kikos, Rishu SharmaAssociate Research Manager, Sharyathi Nagesh, Richard L. VillarsResearch Vice President, Datacenter & Cloud
This IDC FutureScape introduces Asia/Pacific excluding Japan (APEJ) strategic top predictions for 2018 and beyond that will likely impact across enterprises and the time it will take for the predictions to reach the mainstream. It also discusses the confluence of business and ICT trends in order to understand how the necessary alignment within organizations seeking to digitally transform can be created. Each bubble's size provides a rough indicator of the complexity and/or cost an enterprise will incur in acting on the prediction.
The strategic top predictions that will unfold in 2018 and beyond that will have the biggest impact among organizations in Asia/Pacific regarding datacenters are:
- Prediction 1—datacenter modernization. By 2020 in APEJ, the heavy workload demands of next-generation applications and new IT architectures in critical business facilities will have forced 40% of enterprises to modernize their datacenter assets through updates to existing facilities and/or the deployment of new facilities.
- Prediction 2—workload rationalization. By 2019, in APEJ, 30% of organizations will have initiated efforts to rationalize workloads and accelerate the adoption of next-generation cognitive/artificial intelligence (AI), machine learning, and augmented reality (AR), necessitating drastic changes to infrastructure design and placement as well as IT operations models.
- Prediction 3—hybrid IT operations. By the end of 2019, in APEJ, 50% of companies engaged in digital transformation (DX) efforts will be struggling to translate business needs into effective IT investments and operations plans, forcing them to alter staff hiring targets to ensure they have the advanced skill sets needed to build digital supply chains.
- Prediction 4—facilities modularity. By 2021, the expanded use of power-hungry accelerated computing technologies that support cognitive and AI analytics workloads will have forced most major datacenter operators to adopt a modular approach to deploy power/cooling assets in their facilities.
- Prediction 5—consumption-based IT. By 2020, in APEJ, consumption-based procurement in datacenters will have eclipsed traditional procurement through improved as-a-service models, thus accounting for as much as 50% of enterprises' IT infrastructure spending.
- Prediction 6—data controls. By 2021, in APEJ, 20% of large enterprises will have turned mandated regulatory compliance investments to their advantage by using them to set and enforce automated data controls across their cloud, core datacenters, and edge locations.
- Prediction 7—software-defined IT. By the end of 2019, in APEJ, the need for improved agility, better manageability, and enhanced asset usage will force companies pursuing DX to migrate over 35% of their IT infrastructure in their datacenter and edge locations to a software-defined model.
- Prediction 8—smart edge datacenters. By 2021, in APEJ, critical infrastructure in 35% of enterprise datacenters will be operating autonomously, whereas the use of autonomous IT in intelligent edge locations will be even greater as organizations seek to link core and edge resources to support DX initiatives.
- Prediction 9—digital-ready campus. By 2021, in APEJ, over 40% of companies in consumer-facing industries striving to deliver enhanced digital experiences will spend more annually on upgrades to their network, computing, and storage resources in edge locations than on upgrades in their core datacenters.
- Prediction 10—service assurance. In 2019, 60% of digital services will fail to meet desired customer adoption levels because the providers of those services are unable to effectively monitor and quickly respond to performance, utilization, and cost degradations across their diverse IT resource pools.